Data Engineer 2 Interview Experience
My first technical round wasn’t with a person. An AI interviewer ran the whole thing, from logistics questions to reviewing my code line by line.
Interview process
I got in through a referral and then went straight into the first technical round. The surprising part was that it was not a human interviewer on the other side, it was an AI interviewer, so the experience felt different altogether. It started with a few logistics questions, then some technical questions around my work experience, then a 30-minute Python problem, and after that I had around 15 minutes to explain my code and discuss it. I think it went decent. Right now I am just waiting to hear back on whether I get shortlisted for the next round.
- Technical interview
Interview rounds
1 question across 1 roundTechnical interview
1 questionOverview
I went straight into a first-round technical interview that was run by an AI interviewer, which was a different experience altogether. It started with a few logistics questions around my location and whether I could work in a hybrid setup, then some technical questions on my work experience, then a 30-minute Python problem, and after that about 15 minutes where I had to explain my code and discuss it.
Question types asked
Specific questions asked
Define a Python function that takes a baseline schema and incoming records, checks whether they match, and separately flags new fields, missing existing columns, and data type mismatches with the row indexes.
What code-level mistakes or negligence do you see in this solution, and how would you fix them?
Are there any optimizations you can make?
Walk me through how you were thinking about the problem.
I wrote a practical schema-validation function in Python. In the discussion, the AI scanned through my whole code and pointed out small negligence issues. One example was that in a list I had appended four elements at once, and it asked what I should do instead, so I explained the fix. It also asked what optimizations I could do and made me walk through my whole thought process. It felt more like a code review of my solution than just checking whether it ran.
Interview tips
I would definitely prep practical Python questions from a data engineering angle, because this was not some abstract puzzle. Mine was around validating incoming records against a baseline schema and separately flagging new fields, missing columns, and datatype mismatches with row indexes. Also, code carefully because they really can look through the whole solution and catch small negligence mistakes. Then be ready to explain why you wrote it that way and what optimizations you would make, because that discussion is part of the round too.
Company culture
I did not get a huge amount on culture from just one round, but it seemed like a pretty decent, well-established Bangalore startup to me. The product is strong and the customer base also feels strong, since a lot of companies and colleges already use HackerRank. The role itself seemed tied to a hybrid setup, and what I had heard was unlimited leaves plus good compensation.
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